The mechanism behind BAF60c in myocardial metabolism in rats with heart failure is through the PGC1α-PPARα-mTOR signaling pathway
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Metabolic remodeling in heart failure (HF) is a type of overload cardiomyopathy caused by insufficient energy supply or an imbalance of glucose and lipid metabolism. Therefore, metabolic pathways may serve as potential targets for HF treatment. BRM-associated factor (BAF) 60c (also known as smarcd3) promotes the transformation of oxidative muscle fibers to glycolytic muscle fibers. Our study aimed to test whether BAF60c and the PGC1α-PPARα-mTOR pathway interact to affect myocardial metabolism in HF rats. Established rat models of HF were injected with BAF60c low or overexpression plasmids to assess cardiac contractile proteins, energy metabolism, oxidative metabolism, glycolysis, high-energy phosphate content, mitochondrial function, and apoptosis. BAF60c overexpression/siRNA plasmid was transfected into H9C2 cells. These results suggest that HF rats present decreased levels of BAF60c, increased glycolysis, and reduced levels of cardiac contractile proteins, PGC1α, PPARα, and oxidative metabolism. Overexpression of BAF60c maintained the balance between oxidative metabolism and glycolysis and activated the PGC1α-PPARα-mTOR pathway. PGC1α interacted with BAF60c, and overexpression of PGC1α decreased BAF60c knockdown, damaging H9C2 cells. Collectively, overexpression of BAF60c activated the PGC1α-PPARα-mTOR pathway, maintained the oxidative metabolism/glycolysis balance, and improved mitochondrial function in HF rats. This study offers novel insights into HF treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".